Several types of radiation have the ability to penetrate through objects or the body of living creatures. Properly used, these radiations offer non invasive techniques to create an image of the internal structure of different objects of interest, like non-living articles or living bodies. Any penetrating radiation can be used for attenuation-based imaging, if technical solutions to generate, collimate, guide and detect the radiation are available. Probably the most widely used penetrating radiation is x-ray. Other imaging methods may use the attenuation of gamma radiation, visible light, infrared radiation, terahertz radiation, ultrasound, electron beams or ion beams, and further development in this area can be expected. A few of the techniques utilizing these radiations are already well established, while a few are still being developed.
Attenuation-based imaging techniques work by projecting beams of a penetrating radiation through an object of interest. The radiation is generated by a radiation source, and beams of the radiation are usually focused or collimated before passing through the region of the object to be imaged. The radiation is attenuated by the object of interest, and a shadow image (projection) of the region of interest is formed. To record the image, intensity of the emerging attenuated radiation can be detected by a detector, or set of detector elements. These detectors convert the intensity reading into a signal, which can be electronically processed. The image representing the distribution of absorption inside the object of interest can be reconstructed from the recorded intensities.
FIG. 1 (prior art) shows the basic idea of the above image formation process in a flowchart.
Step 102 includes the determination of the attenuation of a penetrating radiation in an object of interest along at least one projection line.
Step 106 includes the reconstruction of the spatial distribution of the attenuation of the object in a viewable image.
Such a simple data acquisition procedure, however, does not allow for the accurate determination of the error of the measured image nor the estimation of the variability of the attenuation inside the body.
One interesting imaging method which uses electron beam as the penetrating radiation is electron microscopy. The transmission electron microscope uses electromagnetic “lenses” to control the electron beam. The electron beam is passed through a specimen and projected on an electron detector to record the shadow image of the specimen. Electron microscopes are used in the study of a broad range of organic specimens including biological specimens such as microorganisms, cells, large molecules, biopsy samples, and of inorganic specimens, including metals and crystals. Environmental electron microscopy is an electron microscopy technique that offers the advantage of visualizing biological samples in their native hydrated state.
Projection images obtained using x-rays (radiographs) have been used in various fields since the discovery of x-rays. For many industrial, medical or research applications recording an x-ray shadow along one projection direction may be enough. In many uses, however, a more detailed three dimensional image of the object of interest may be desirable. Computed tomography (CT) combines several projections recorded from different directions (angles of view) to produce cross section images of the object of interest. The cross section images can be used to reconstruct a 3D image of the object of study. The created 3D or cross section images are typically visualized on a computer screen, printed, or reproduced on a film.
Computed tomography is widely used in industry, research and also in medical imaging. In medical applications, the difference of the absorbance of different tissues gives enough contrast for the adequate diagnosis in many cases. If the contrast between different tissues is not enough, contrast agents are used to facilitate the examination.
To describe the absorption and detection of different radiations it may be useful to think about radiation as particles. The particles of the electromagnetic waves are called photons. In the case of electron or ion beams the particle nature of the radiation is more obvious. The radiation intensity falling on a detector is proportional to the number of particles reaching the detector in unit time. The particle count reading of a detector, however, may vary even if the intensity falling on the detector is constant. The actual number of counted particles fluctuates around an average according to Poisson distribution resulting in the so called shot noise. This effect introduces a theoretically unavoidable inaccuracy in the intensity measurements of several penetrating radiations. Further error of the measured values can be caused by other factors, such as instrument noise. Depending on radiation type, and the contribution of different noise sources, the resulting measurements can have different distribution around a mean value. Poisson and Gaussian (normal) distributions were shown to occur in many cases.
Several prior art patent documents try to identify motions in acquired projections. The aim of these works is to find projections which are recorded in a specific phase of the motion (U.S. Pat. No. 7,085,342 to Younis et al.), to remove motion artifacts from the images (U.S. Pat. No. 6,535,570 to Stergiopuolos et al., U.S. Pat. No. 6,879,656 to Cesmeli et al.), or to calculate physiologically interesting characteristics of the heart (U.S. Pat. No. 6,421,552 to Hsieh). All the techniques taught in these prior art documents are limited to extracting a few characteristics of a periodically moving organ and produce motion artifact corrected series of still images.
Other prior art patent documents aim at minimizing the effect of the measurement error on the reconstructed image. One advantage of better image quality is the possibility of reducing the radiation dose used in imaging. Often, the published methods of the prior art allow an estimation of the error of the image as well. The disadvantage of these prior art methods, however, is that they are based on theoretical estimations of the variability of the measured data, rather than on a direct measurement.
In U.S. Pat. No. 7,356,174, Leue and coworkers describe a method to estimate the effect of the inaccuracy of the x-ray detection on a reconstructed image. The method described in this patent suffers from several shortcomings. The method is designed only for situations in which the imaged x-ray densities are time independent, and assumes that measured photon counts follow Poisson distribution. The method of Leue and coworkers is not able to reconstruct the image of any attenuation fluctuations of the object. In fact, such attenuation changes may lead to less accurate image reconstruction by the above method, and/or less accurate estimation of the error of the image.
In U.S. Pat. No. 7,187,794, Liang and coworkers describe a method for treating noise in low-dose computed tomography applications. After analyzing repeatedly recorded phantom scan datasets, Liang et al. conclude that in their case the noise is close to a normal distribution. Using the information acquired in the absence of a patient, this group proposes a means to lower the effect of noise on the reconstructed image of the patient. The method of Liang and coworkers is designed to image static structures, thus it can not visualize motions or fluctuations in the x-ray attenuation. Moreover, image reconstruction may become less reliable in the presence of such changes of attenuation.
The method published by Fessler (U.S. Pat. No. 6,754,298) reconstructs an image from a plurality of projection data recorded at different x-ray photon energy distributions. Similarly to the two patents described above, this technique also assumes a static object of study, and the gained image may deteriorate if this assumption is violated.
In U.S. Pat. No. 7,103,204, Celler and coworkers publish a method to track changes in the photon emission of an object. Their main purpose, however, is to represent movements as a series of image frames, rather than to determine the extent of movements in the pixels. Also, the method works on emission-based imaging techniques, and not transmission measurements.
In U.S. Pat. Appl. No. 2005/0,226,484, Basu and coworkers publish a method to estimate the variance of generated 3D CT images. Their method starts from the assumption that the variance originates only in the noise of the measurement which is dominated by the photon shot noise. As a consequence of this assumption, the method described in U.S. Pat. Appl. No. 2005/0,226,484 is incapable of generating images representing the attenuation fluctuation of the object of interest.
Many image processing methods (e.g. U.S. Pat. No. 6,256,403 to Florent and coworkers) calculate the pixel variance of images from the neighborhood of the given pixel. The result of such calculations reflects the variance of the image along the space coordinates in a certain region, and can not represent time dependent fluctuations.
In U.S. Pat. No. 6,169,817, Parker and coworkers describe a method of 4D (space and time) visualization of image data. Spatial (regional) variance is calculated for individual image frames to determine connectivity of pixels in the image. Temporal changes are represented as a series of consecutive still images. This method is also incapable to represent attenuation fluctuations.
Patent No. EP 1,959,397 to O'Halloran and coworkers focuses on the removal of motion artifacts from images. The method uses HYPR reconstruction to represent the imaged object as a snapshot taken at different times during the motion. This method focuses on removal of motion artifacts to generate still images, and it is not designed to represent local fluctuations.